title: Automated analysis of intima-media thickness: analysis and performance of CARES 3.0.
abstract: OBJECTIVE
  In recent years, the use of computer-based techniques has been advocated to improve intima-media thickness (IMT) quantification and its reproducibility. The purpose of this study was to test the diagnostic performance of a new IMT automated algorithm, CARES 3.0, which is a patented class of IMT measurement systems called AtheroEdge (AtheroPoint, LLC, Roseville, CA).
  
  
  METHODS
  From 2 different institutions, we analyzed the carotid arteries of 250 patients. The automated CARES 3.0 algorithm was tested versus 2 other automated algorithms, 1 semiautomated algorithm, and a reader reference to assess the IMT measurements. Bland-Altman analysis, regression analysis, and the Student t test were performed.
  
  
  RESULTS
  CARES 3.0 showed an IMT measurement bias ± SD of -0.022 ± 0.288 mm compared with the expert reader. The average IMT by CARES 3.0 was 0.852 ± 0.248 mm, and that of the reader was 0.872 ± 0.325 mm. In the Bland-Altman plots, the CARES 3.0 IMT measurements showed accurate values, with about 80% of the images having an IMT measurement bias ranging between -50% and +50%. These values were better than those of the previous CARES releases and the semiautomated algorithm. Regression analysis showed that, among all techniques, the best t value was between CARES 3.0 and the reader.
  
  
  CONCLUSIONS
  We have developed an improved fully automated technique for carotid IMT measurement on longitudinal ultrasound images. This new version, called CARES 3.0, consists of a new heuristic for lumen-intima and media-adventitia detection, which showed high accuracy and reproducibility for IMT measurement.
authors.affiliation: Department of Radiology, Azienda Ospedaliero Universitaria di Cagliari-Polo di Monserrato, SS 554 Monserrato, 09045 Cagliari, Italy. lucasaba@tiscali.it
authors.forename: Luca
authors.initials: L
authors.lastname: Saba
authors.forename: Roberto
authors.initials: R
authors.lastname: Montisci
authors.forename: Luca
authors.initials: L
authors.lastname: Famiglietti
authors.forename: Niranjan
authors.initials: N
authors.lastname: Tallapally
authors.forename: U Rajendra
authors.initials: UR
authors.lastname: Acharya
authors.forename: Filippo
authors.initials: F
authors.lastname: Molinari
authors.forename: Roberto
authors.initials: R
authors.lastname: Sanfilippo
authors.forename: Giorgio
authors.initials: G
authors.lastname: Mallarini
authors.forename: Andrew
authors.initials: A
authors.lastname: Nicolaides
authors.forename: Jasjit S
authors.initials: JS
authors.lastname: Suri
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D002339:Carotid Arteries / Q000000981:diagnostic imaging*; D002340:Carotid Artery Diseases / Q000000981:diagnostic imaging* / Q000453:epidemiology*; D059168:Carotid Intima-Media Thickness; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007558:Italy / Q000453:epidemiology; D008297:Male; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods / Q000706:statistics & numerical data; D015203:Reproducibility of Results; D012307:Risk Factors; D012680:Sensitivity and Specificity; D012984:Software; D012986:Software Validation
keywords: automated algorithm; carotid artery; intima-media thickness